Zusammenfassung / Abstract

The number of elderly people in our societies is increasing steadily. Most of the times, these elderly people like to live alone in their homes which gives them a sense of ownership and control over their lives. This growing trend has led many researchers to develop robotic platforms to assist elderly people in their daily life activities at their homes. To serve an elderly person at home, it is necessary that the mobile robot approaches the human to initiate an interaction or inquire about any services. Mostly it is done by pre-defining some locations in the home environment and the robot is called upon by the elderly person at these locations. In such scenarios, the robot behaves as a reactive device which waits for a signal to navigate to a specific location.

The aim of this thesis is to develop a methodology which enables an autonomous indoor mobile robot to pro-actively search an elderly person in a home environment. Besides being helpful in scenarios like initiating communication, or reminding an event, such pro-active approach is essentially required in scenarios of autonomously detecting an emergency situation where the person might not be able to call the robot for help. The developed methodology is inspired from human behavior during the search of lost objects or fellow humans, which relies on several factors. Among those, the most prominent one is that they learn from their experience where a fellow human is usually seen at a particular time of the day. This learned knowledge makes the search process much faster as compared to searching randomly or everywhere in the living environment. The proposed search methodology is based on the same concept. In order to develop the cognition of presence of person in the environment, several locations are computed by the robot which gives best possibility to observe the environment and find the person at different times of the day.

The experiments in real environment as well as in simulation show that the mobile robot, ARTOS, autonomously and pro-actively initiates the search process and traverse to different locations in the home environment to find the human. The results show that with the passage of time, the robot successfully learns the daily routine of the person and uses this information to expedite the search process. A promising success percentage of more than 90% of finding the human shows the effectiveness of the proposed methodology.